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Messages - msingh96

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Woah that's convenient!  8)  I came up with a pretty blunt way to extract the values in the end but will probably switch to this!

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There's a decently old topic about exporting an MD trajectory to the xyz format. however it would also be helpful to export using the ASE package bundled with atk python. but I'm kind of lost on how to use ASE with QuantumATK. how do I load the MD trajectory, I want all of the data mind you, into atoms objects to export the data to external formats? exporting to trainingsets, then table is probably not what I want to do.

Mayur

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Hi Anders, this was really helpful. I got an active learning workflow to actually "work" now. Now for some tuning and fidgeting with the parameters. some followup questions:
  • The calculator used is typically a DFT calculator, I guess this means that we simply train a new MTP. In the active learning parameters it is possible to manually set a reference calculator and a correction calculator, I'm wondering if it is possible to use an existing MTP for active learning to "retrain" or improve the results of the MTP by using these settings?
  • what parameters are the usual suspects if trying to perform a sensitivity analysis on the active learning and regular training of the MTP?

Regards and thanks for the assistance,
Mayur

4
Hi Anders, thank you for the insight. However, I cant seem to get the active learning blocks set up for what the example suggests. When I insert an ActiveLearningSimulation block I get an error saying that I have not provided configurations or initial training data to perform the job.
I'm messing up something completely novice here, but I'm not very familiar with the custom scripting in quantumATK I'm attaching some pictures of my workflow and hopefully that is informative.

Thanks again, Mayur

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Hi has anyone used active learning in the new version of QuantumATK before?

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Hello, I'm trying to use the active learning simulation methods but am having trouble setting up workflows to go forward. the active learning blocks tell me an initial training data set of type table was not provided... so I tried exporting existing trajectories from an MD simulation I had done with an MTP as table... but I'm fairly clueless as to exporting an existing table or old trajectory data to the workflow manager. the tutorials for active learning in the documentation do not use the new GUI, so I wasn't able to find much help there.
I'm sure there are concepts I'm not understanding but what I am trying to do is as follows:

  • Train an initial MLP using crystal training template, which is based on tutorial for HfO2
  • Generate additional training using fitted MTP in MD simulation
  • Active Learning on the data from MD.

I'm having trouble with the 3rd step of this list, how do I export the trajectories along with the energies and forces from my MD simulation to the active learning format?

Thanks, Mayur

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Hello. I think I figured it out. the distance between surfaces in the initial geometry was too close, causing large forces to explode and break most structures.

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Hi Anders, I've been trying to figure this out on my own before posting again.

I am trying to use the Si/TiSi2 potential for MD simulations. I have had modest success with small structures, but the most frequent error is atoms leaving the simulation cell. this error causes the MD simulation to stall and get stuck. my instinct is an issue with the structures I provided, I used the interface builder to make an initial structure with Si [100] surface and TiSi[001] surface but I have to manually modify the distance between the surfaces using shift surface. I want to equilibrate the surface distance suing NPT but that's not working either.

Are there any example geometries from the training data for this potential to see where I'm going wrong?

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Hello QuantumATK users, this is my first post in the forum. I have started using QuantumATK for the MTP functionality it provides as advertised here: https://www.synopsys.com/manufacturing/quantumatk/atomistic-simulation-products/machine-learned-force-fields.html.

One exciting thing I found was the library of pretrained MTPs made available for users: https://docs.quantumatk.com/manual/ForceField.html#pretrained-moment-tensor-potential-mtp-parameter-sets

However I am struggling to use these effectively. I am running into two errors.
1. the nose-hoover thermostats seem to fail/atoms seem to explode for certain interfaces
2. atoms leave simulation regime and MD simulation stalls.

I am wondering if there are any examples or  information about the training data (structures) for these pretrained potentials.

Regards and Thanks, Mayur

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